Import and process data

Learning

Model: Correct responses by age, trial, block number, and block condition

	correct_response_made
Predictors	Odds Ratios	CI
age group1	0.7626	0.6622 – 0.8782
learning trial scaled	1.4490	1.3633 – 1.5401
reward condition1	1.8834	1.6788 – 2.1128
block number scaled	1.1543	1.0776 – 1.2364
age group1 × learning trial scaled	0.8999	0.8469 – 0.9563
age group1 × reward condition1	0.8880	0.7917 – 0.9960
learning trial scaled × reward condition1	1.1825	1.1280 – 1.2397
age group1 × block number scaled	1.0190	0.9513 – 1.0914
learning trial scaled × block number scaled	1.0280	0.9953 – 1.0618
reward condition1 × block number scaled	1.0688	0.9982 – 1.1444
age group1 × learning trial scaled × reward condition1	0.9677	0.9232 – 1.0142
(age group1 × learning trial scaled) × block number scaled	0.9944	0.9628 – 1.0271
(age group1 × reward condition1) × block number scaled	1.0521	0.9827 – 1.1265
(learning trial scaled × reward condition1) × block number scaled	0.9987	0.9648 – 1.0338
(age group1 × learning trial scaled × reward condition1) × block number scaled	1.0168	0.9823 – 1.0526
Random Effects
σ²	3.29
τ₀₀ _{subject_id}	0.36
τ₁₁ _{subject_id.re1.learning_trial_scaled}	0.06
τ₁₁ _{subject_id.re1.reward_condition1}	0.23
τ₁₁ _{subject_id.re1.block_number_scaled}	0.08
τ₁₁ _{subject_id.re1.learning_trial_scaled_by_reward_condition1}	0.03
τ₁₁ _{subject_id.re1.learning_trial_scaled_by_block_number_scaled}	0.01
τ₁₁ _{subject_id.re1.reward_condition1_by_block_number_scaled}	0.07
τ₁₁ _{subject_id.re1.learning_trial_scaled_by_reward_condition1_by_block_number_scaled}	0.01
ρ₀₁
ρ₀₁
ICC	0.10
N _{subject_id}	73
Observations	31536
Marginal R² / Conditional R²	0.163 / 0.246

Figure 5A: Correct response by block condition, stimulus repetition, and age group

Supplementary Figure: Correct response by block condition and block number

Figure 5B: Generalization by block condition, category repetition, age group

Model: Correct response to first appearance of each stimulus

	correct_response_made
Predictors	Odds Ratios	CI
age group1	0.9285	0.8550 – 1.0082
category rep scaled	1.1209	1.0447 – 1.2027
reward condition1	1.4819	1.3557 – 1.6199
block number scaled	1.0176	0.9481 – 1.0923
age group1 × category rep scaled	1.0128	0.9439 – 1.0866
age group1 × reward condition1	0.8858	0.8104 – 0.9681
category rep scaled × reward condition1	1.2599	1.1740 – 1.3521
age group1 × block number scaled	0.9790	0.9121 – 1.0509
category rep scaled × block number scaled	1.0071	0.9402 – 1.0787
reward condition1 × block number scaled	1.0774	0.9886 – 1.1743
age group1 × category rep scaled × reward condition1	0.9448	0.8805 – 1.0137
(age group1 × category rep scaled) × block number scaled	0.9514	0.8882 – 1.0190
(age group1 × reward condition1) × block number scaled	1.0205	0.9363 – 1.1122
(category rep scaled × reward condition1) × block number scaled	0.9952	0.9292 – 1.0660
(age group1 × category rep scaled × reward condition1) × block number scaled	1.0032	0.9366 – 1.0745
Random Effects
σ²	3.29
τ₀₀ _{subject_id}	0.04
τ₁₁ _{subject_id.re1.reward_condition1}	0.06
τ₁₁ _{subject_id.re1.block_number_scaled}	0.01
τ₁₁ _{subject_id.re1.reward_condition1_by_block_number_scaled}	0.05
ρ₀₁
ρ₀₁
ICC	0.01
N _{subject_id}	73
Observations	3942
Marginal R² / Conditional R²	0.073 / 0.085

Model: Category win-stay lose-shift

	WSLS
Predictors	Odds Ratios	CI
age group1	0.9060	0.8502 – 0.9655
learning trial scaled	1.0102	0.9819 – 1.0392
reward condition1	1.5157	1.4195 – 1.6185
block number scaled	1.0603	1.0183 – 1.1039
age group1 × learning trial scaled	0.9983	0.9704 – 1.0270
age group1 × reward condition1	0.8968	0.8399 – 0.9575
learning trial scaled × reward condition1	1.1446	1.1085 – 1.1820
age group1 × block number scaled	1.0197	0.9794 – 1.0617
learning trial scaled × block number scaled	0.9811	0.9555 – 1.0073
reward condition1 × block number scaled	1.0701	1.0329 – 1.1087
age group1 × learning trial scaled × reward condition1	0.9802	0.9493 – 1.0122
(age group1 × learning trial scaled) × block number scaled	1.0132	0.9868 – 1.0403
(age group1 × reward condition1) × block number scaled	1.0053	0.9704 – 1.0415
(learning trial scaled × reward condition1) × block number scaled	1.0040	0.9775 – 1.0312
(age group1 × learning trial scaled × reward condition1) × block number scaled	1.0141	0.9873 – 1.0416
Random Effects
σ²	3.29
τ₀₀ _{subject_id}	0.06
τ₁₁ _{subject_id.re1.learning_trial_scaled}	0.00
τ₁₁ _{subject_id.re1.reward_condition1}	0.07
τ₁₁ _{subject_id.re1.block_number_scaled}	0.02
τ₁₁ _{subject_id.re1.learning_trial_scaled_by_reward_condition1}	0.01
τ₁₁ _{subject_id.re1.learning_trial_scaled_by_block_number_scaled}	0.00
τ₁₁ _{subject_id.re1.reward_condition1_by_block_number_scaled}	0.01
τ₁₁ _{subject_id.re1.learning_trial_scaled_by_reward_condition1_by_block_number_scaled}	0.00
ρ₀₁
ρ₀₁
ICC	0.02
N _{subject_id}	73
Observations	29799
Marginal R² / Conditional R²	0.064 / 0.082

Supplementary Figure: WSLS by age group

Supplementary Figure: WSLS by block number

Memory

Overall descriptive memory stats

mean_mem	se_mem
0.7579	0.01331

Memory delay stats

mean_delay	sd_delay	min_delay	max_delay
7.123	1.092	5	10

age_group	mean_delay	sd_delay	min_delay	max_delay
Children	7.118	1.122	6	10
Adults	7.128	1.08	5	9

memory_delay	age_group	N
5	Adults	1
6	Children	13
6	Adults	13
7	Children	9
7	Adults	9
8	Children	8
8	Adults	12
9	Children	3
9	Adults	4
10	Children	1

Figure 5D: AUC values by age group, memory specificity, block condition

Model: AUCs by age group, reward condition, memory specificity

	AUC
Predictors	Estimates	CI
age group1	-0.0029	-0.0310 – 0.0252
reward condition1	-0.0179	-0.0258 – -0.0100
foil type1	0.0428	0.0349 – 0.0507
age group1 × reward condition1	-0.0006	-0.0085 – 0.0073
age group1 × foil type1	0.0036	-0.0043 – 0.0115
reward condition1 × foil type1	0.0078	-0.0001 – 0.0157
age group1 × reward condition1 × foil type1	0.0031	-0.0048 – 0.0110
Random Effects
σ²	0.00
τ₀₀ _{subject_id}	0.01
ICC	0.74
N _{subject_id}	73
Observations	292
Marginal R² / Conditional R²	0.108 / 0.772

Model: AUCs by age, reward condition, foil type, delay

	AUC
Predictors	Estimates	CI
age group1	-0.0029	-0.0314 – 0.0256
reward condition1	-0.0180	-0.0258 – -0.0101
foil type1	0.0428	0.0349 – 0.0506
mem delay scaled	0.0035	-0.0250 – 0.0320
age group1 × reward condition1	-0.0006	-0.0084 – 0.0073
age group1 × foil type1	0.0037	-0.0042 – 0.0115
reward condition1 × foil type1	0.0078	-0.0001 – 0.0156
age group1 × mem delay scaled	0.0037	-0.0248 – 0.0323
reward condition1 × mem delay scaled	-0.0001	-0.0080 – 0.0077
foil type1 × mem delay scaled	0.0097	0.0019 – 0.0176
age group1 × reward condition1 × foil type1	0.0031	-0.0047 – 0.0110
(age group1 × reward condition1) × mem delay scaled	-0.0065	-0.0143 – 0.0014
(age group1 × foil type1) × mem delay scaled	0.0032	-0.0046 – 0.0111
(reward condition1 × foil type1) × mem delay scaled	-0.0001	-0.0079 – 0.0078
(age group1 × reward condition1 × foil type1) × mem delay scaled	0.0021	-0.0058 – 0.0099
Random Effects
σ²	0.00
τ₀₀ _{subject_id}	0.01
ICC	0.75
N _{subject_id}	73
Observations	292
Marginal R² / Conditional R²	0.114 / 0.782

Supplementary Figure: AUC values with delay

RL modeling

Choice weights

Figure: Distribution of choice weights

Figure 5C: Choice weights box plot

Model: Choice weights by block condition and age group

	est
Predictors	Estimates	CI
abstraction1	-0.0404	-0.1481 – 0.0673
reward condition1	0.0417	-0.0660 – 0.1494
age group1	-0.0842	-0.2771 – 0.1087
abstraction1 × reward condition1	0.1356	0.0279 – 0.2433
abstraction1 × age group1	0.0967	-0.0110 – 0.2044
reward condition1 × age group1	0.0157	-0.0920 – 0.1234
abstraction1 × reward condition1 × age group1	-0.0347	-0.1424 – 0.0730
Random Effects
σ²	0.87
τ₀₀ _{subject_id}	0.48
ICC	0.36
N _{subject_id}	73
Observations	292
Marginal R² / Conditional R²	0.029 / 0.375

Model: Exemplar choice weights by condition

	est
Predictors	Estimates	CI
reward condition1	-0.0974	-0.2172 – 0.0224
Random Effects
σ²	0.54
τ₀₀ _{subject_id}	0.87
ICC	0.62
N _{subject_id}	73
Observations	146
Marginal R² / Conditional R²	0.007 / 0.622

Model: Category choice weights by condition

	est
Predictors	Estimates	CI
reward condition1	0.1785	0.0517 – 0.3054
Random Effects
σ²	0.60
τ₀₀ _{subject_id}	0.69
ICC	0.54
N _{subject_id}	73
Observations	146
Marginal R² / Conditional R²	0.024 / 0.546

Model: Relation between exemplar and category choice weights

	beta_e_scaled
Predictors	Estimates	CI
beta c scaled	-0.0181	-0.1745 – 0.1383
age scaled	0.1214	-0.0939 – 0.3367
block condition1	-0.0752	-0.1725 – 0.0221
beta c scaled × age scaled	-0.1044	-0.2659 – 0.0571
beta c scaled × block condition1	-0.1448	-0.2517 – -0.0379
age scaled × block condition1	-0.0146	-0.1150 – 0.0858
beta c scaled × age scaled × block condition1	0.0345	-0.0728 – 0.1418
Random Effects
σ²	0.33
τ₀₀ _{subject_id}	0.69
ICC	0.67
N _{subject_id}	73
Marginal R² / Conditional R²	0.057 / 0.692

## 
## Call:
## lm(formula = beta_e_scaled ~ beta_c_scaled * age_scaled, data = beta_ests_wide_exemp_pred)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.4370 -0.4634  0.1487  0.6339  1.7488 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)  
## (Intercept)              -0.0002356  0.1131188  -0.002    0.998  
## beta_c_scaled             0.2815002  0.1150579   2.447    0.017 *
## age_scaled                0.1871373  0.1156527   1.618    0.110  
## beta_c_scaled:age_scaled -0.0038982  0.1173137  -0.033    0.974  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9646 on 69 degrees of freedom
## Multiple R-squared:  0.1083, Adjusted R-squared:  0.06957 
## F-statistic: 2.795 on 3 and 69 DF,  p-value: 0.04666

	beta_e_scaled
Predictors	Estimates	CI
beta c scaled	0.2815	0.0520 – 0.5110
age scaled	0.1871	-0.0436 – 0.4179
beta c scaled × age scaled	-0.0039	-0.2379 – 0.2301
Observations	73
R² / R² adjusted	0.108 / 0.070

## 
## Call:
## lm(formula = beta_e_scaled ~ beta_c_scaled * age_scaled, data = beta_ests_wide_cat_pred)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.19715 -0.79074  0.04502  0.83269  1.78719 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)
## (Intercept)               3.404e-05  1.182e-01   0.000    1.000
## beta_c_scaled             1.039e-01  1.196e-01   0.869    0.388
## age_scaled                1.021e-01  1.197e-01   0.853    0.397
## beta_c_scaled:age_scaled -2.219e-02  1.210e-01  -0.183    0.855
## 
## Residual standard error: 1.01 on 69 degrees of freedom
## Multiple R-squared:  0.02178,    Adjusted R-squared:  -0.02075 
## F-statistic: 0.5121 on 3 and 69 DF,  p-value: 0.6753

	beta_e_scaled
Predictors	Estimates	CI
beta c scaled	0.1039	-0.1347 – 0.3425
age scaled	0.1021	-0.1367 – 0.3410
beta c scaled × age scaled	-0.0222	-0.2636 – 0.2192
Observations	73
R² / R² adjusted	0.022 / -0.021

Relations between choice weights and points earned

## Mixed Model Anova Table (Type 3 tests, S-method)
## 
## Model: total_points ~ age_group * beta_scaled * abstraction * reward_condition + 
## Model:     (1 | subject_id)
## Data: beta_ests_points
##                                                Effect        df          F
## 1                                           age_group  1, 60.48  15.36 ***
## 2                                         beta_scaled 1, 267.98   10.74 **
## 3                                         abstraction 1, 195.18       0.69
## 4                                    reward_condition 1, 194.54 451.24 ***
## 5                               age_group:beta_scaled 1, 267.98       0.27
## 6                               age_group:abstraction 1, 195.18       0.00
## 7                             beta_scaled:abstraction 1, 227.31       0.38
## 8                          age_group:reward_condition 1, 194.54     4.69 *
## 9                        beta_scaled:reward_condition 1, 203.34  31.13 ***
## 10                       abstraction:reward_condition 1, 195.93       0.09
## 11                  age_group:beta_scaled:abstraction 1, 227.31       0.23
## 12             age_group:beta_scaled:reward_condition 1, 203.34       0.39
## 13             age_group:abstraction:reward_condition 1, 195.93       0.00
## 14           beta_scaled:abstraction:reward_condition 1, 208.19  30.89 ***
## 15 age_group:beta_scaled:abstraction:reward_condition 1, 208.19       1.49
##    p.value
## 1    <.001
## 2     .001
## 3     .407
## 4    <.001
## 5     .604
## 6     .946
## 7     .538
## 8     .032
## 9    <.001
## 10    .762
## 11    .631
## 12    .532
## 13    .979
## 14   <.001
## 15    .224
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	total_points
Predictors	Estimates	CI
age group1	-15.8448	-23.7681 – -7.9216
beta scaled	8.0743	3.2461 – 12.9026
abstraction1	-1.5690	-5.2683 – 2.1302
reward condition1	40.0446	36.3499 – 43.7394
age group1 × beta scaled	1.2807	-3.5475 – 6.1090
age group1 × abstraction1	-0.1289	-3.8281 – 3.5704
beta scaled × abstraction1	1.3196	-2.8691 – 5.5083
age group1 × reward condition1	-4.0809	-7.7756 – -0.3861
beta scaled × reward condition1	10.9521	7.1050 – 14.7991
abstraction1 × reward condition1	-0.5741	-4.2797 – 3.1314
age group1 × beta scaled × abstraction1	-1.0283	-5.2170 – 3.1604
age group1 × beta scaled × reward condition1	-1.2295	-5.0765 – 2.6175
age group1 × abstraction1 × reward condition1	-0.0497	-3.7552 – 3.6558
beta scaled × abstraction1 × reward condition1	11.1124	7.1938 – 15.0309
age group1 × beta scaled × abstraction1 × reward condition1	-2.4386	-6.3572 – 1.4799
Random Effects
σ²	994.76
τ₀₀ _{subject_id}	928.76
ICC	0.48
N _{subject_id}	73
Marginal R² / Conditional R²	0.538 / 0.761

## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_c_c)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -93.64 -36.87   3.86  39.43  83.93 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   36.795      5.880   6.257 2.62e-08 ***
## est           39.829      4.692   8.489 2.07e-12 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 46.65 on 71 degrees of freedom
## Multiple R-squared:  0.5037, Adjusted R-squared:  0.4968 
## F-statistic: 72.07 on 1 and 71 DF,  p-value: 2.069e-12

	total_points
Predictors	Estimates	CI
est	39.8290	30.4742 – 49.1838
Observations	73
R² / R² adjusted	0.504 / 0.497

## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_e_c)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -131.981  -52.267   -2.401   41.211  143.996 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   50.653      7.626   6.642 5.28e-09 ***
## est           16.470      6.364   2.588   0.0117 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 63.31 on 71 degrees of freedom
## Multiple R-squared:  0.0862, Adjusted R-squared:  0.07333 
## F-statistic: 6.698 on 1 and 71 DF,  p-value: 0.0117

	total_points
Predictors	Estimates	CI
est	16.4696	3.7804 – 29.1587
Observations	73
R² / R² adjusted	0.086 / 0.073

## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_c_e)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -64.897 -23.138  -3.735  21.206  87.594 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -24.448      4.025  -6.074 5.56e-08 ***
## est           -6.766      3.665  -1.846    0.069 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 34.22 on 71 degrees of freedom
## Multiple R-squared:  0.04581,    Adjusted R-squared:  0.03237 
## F-statistic: 3.408 on 1 and 71 DF,  p-value: 0.06904

	total_points
Predictors	Estimates	CI
est	-6.7664	-14.0745 – 0.5416
Observations	73
R² / R² adjusted	0.046 / 0.032

## 
## Call:
## lm(formula = total_points ~ est, data = beta_ests_points_e_e)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -63.454 -13.244  -2.002  14.115  72.974 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -34.370      3.306 -10.395 6.60e-16 ***
## est           19.236      2.576   7.468 1.62e-10 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 26.22 on 71 degrees of freedom
## Multiple R-squared:  0.4399, Adjusted R-squared:  0.432 
## F-statistic: 55.77 on 1 and 71 DF,  p-value: 1.616e-10

	total_points
Predictors	Estimates	CI
est	19.2355	14.0996 – 24.3715
Observations	73
R² / R² adjusted	0.440 / 0.432

Supplementary Figure: Points earned vs. beta values

Relations between learning and memory

Do points earned during learning relate to memory?

Model: AUC by points earned, reward condition, age group

	AUC
Predictors	Estimates	CI
age group1	0.0000	-0.0281 – 0.0281
points scaled	0.0403	0.0198 – 0.0608
abstraction1	0.0316	0.0195 – 0.0437
reward condition1	-0.0397	-0.0554 – -0.0240
age group1 × points scaled	0.0011	-0.0194 – 0.0217
age group1 × abstraction1	0.0020	-0.0101 – 0.0142
points scaled × abstraction1	-0.0030	-0.0165 – 0.0105
age group1 × reward condition1	-0.0021	-0.0178 – 0.0136
points scaled × reward condition1	-0.0135	-0.0305 – 0.0034
abstraction1 × reward condition1	0.0098	-0.0023 – 0.0219
age group1 × points scaled × abstraction1	-0.0112	-0.0247 – 0.0023
age group1 × points scaled × reward condition1	0.0108	-0.0061 – 0.0278
age group1 × abstraction1 × reward condition1	0.0133	0.0012 – 0.0254
points scaled × abstraction1 × reward condition1	0.0139	0.0004 – 0.0274
age group1 × points scaled × abstraction1 × reward condition1	0.0024	-0.0111 – 0.0159
Random Effects
σ²	0.00
τ₀₀ _{subject_id}	0.01
ICC	0.71
N _{subject_id}	73
Observations	292
Marginal R² / Conditional R²	0.164 / 0.754

Figure 5E: AUC by performance group and reward condition

Do choice weights relate to memory?

Model: AUC by age group, exemplar choice weights, specificity, block condition

	AUC
Predictors	Estimates	CI
age group1	0.0027	-0.0214 – 0.0269
beta scaled	0.0345	0.0189 – 0.0500
abstraction1	0.0431	0.0350 – 0.0513
reward condition1	-0.0136	-0.0219 – -0.0053
age group1 × beta scaled	-0.0159	-0.0315 – -0.0004
age group1 × abstraction1	0.0039	-0.0043 – 0.0121
beta scaled × abstraction1	0.0015	-0.0067 – 0.0097
age group1 × reward condition1	-0.0035	-0.0118 – 0.0048
beta scaled × reward condition1	-0.0018	-0.0108 – 0.0072
abstraction1 × reward condition1	0.0079	-0.0002 – 0.0161
age group1 × beta scaled × abstraction1	0.0020	-0.0062 – 0.0102
age group1 × beta scaled × reward condition1	0.0061	-0.0029 – 0.0151
age group1 × abstraction1 × reward condition1	0.0034	-0.0048 – 0.0115
beta scaled × abstraction1 × reward condition1	0.0010	-0.0072 – 0.0091
age group1 × beta scaled × abstraction1 × reward condition1	0.0008	-0.0074 – 0.0090
Random Effects
σ²	0.00
τ₀₀ _{subject_id}	0.01
ICC	0.66
N _{subject_id}	73
Observations	292
Marginal R² / Conditional R²	0.203 / 0.733

Figure 5F: AUC by exemplar choice weights: model effects

Model: AUC by age group, category choice weights, specificity, block condition

	AUC
Predictors	Estimates	CI
age group1	-0.0048	-0.0332 – 0.0236
beta scaled	0.0083	-0.0063 – 0.0230
abstraction1	0.0423	0.0345 – 0.0501
reward condition1	-0.0192	-0.0272 – -0.0112
age group1 × beta scaled	0.0094	-0.0053 – 0.0240
age group1 × abstraction1	0.0040	-0.0037 – 0.0118
beta scaled × abstraction1	0.0111	0.0033 – 0.0190
age group1 × reward condition1	-0.0019	-0.0099 – 0.0061
beta scaled × reward condition1	0.0011	-0.0078 – 0.0101
abstraction1 × reward condition1	0.0061	-0.0017 – 0.0138
age group1 × beta scaled × abstraction1	-0.0013	-0.0092 – 0.0065
age group1 × beta scaled × reward condition1	0.0115	0.0026 – 0.0204
age group1 × abstraction1 × reward condition1	0.0035	-0.0043 – 0.0113
beta scaled × abstraction1 × reward condition1	0.0025	-0.0054 – 0.0104
age group1 × beta scaled × abstraction1 × reward condition1	-0.0031	-0.0110 – 0.0047
Random Effects
σ²	0.00
τ₀₀ _{subject_id}	0.01
ICC	0.76
N _{subject_id}	73
Observations	292
Marginal R² / Conditional R²	0.126 / 0.789

Figure 5F: AUC by category choice weights: model effects

Relations between age group and other model parameters

Model: Alpha choice values by age group

## 
## Call:
## lm(formula = alpha ~ age_group, data = param_ests)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.9662 -1.6183 -0.4774  1.8037  5.2505 
## 
## Coefficients:
##                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)      -3.6116     0.3407 -10.600 2.82e-16 ***
## age_groupAdults   0.3878     0.4661   0.832    0.408    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.987 on 71 degrees of freedom
## Multiple R-squared:  0.009655,   Adjusted R-squared:  -0.004293 
## F-statistic: 0.6922 on 1 and 71 DF,  p-value: 0.4082

Model: Alpha cf values by age group

## 
## Call:
## lm(formula = alpha_cf ~ age_group, data = param_ests)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.2676 -0.5954  0.4327  1.1856  4.0781 
## 
## Coefficients:
##                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)      -1.9938     0.3326  -5.995 7.69e-08 ***
## age_groupAdults   0.1240     0.4550   0.273    0.786    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.939 on 71 degrees of freedom
## Multiple R-squared:  0.001045,   Adjusted R-squared:  -0.01302 
## F-statistic: 0.07431 on 1 and 71 DF,  p-value: 0.786

Model: Initial Q by age

## 
## Call:
## lm(formula = q_init ~ age_group, data = param_ests)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -6.895 -2.615  1.736  2.309  2.962 
## 
## Coefficients:
##                 Estimate Std. Error t value Pr(>|t|)   
## (Intercept)       1.4896     0.5168   2.882  0.00522 **
## age_groupAdults  -0.2880     0.7071  -0.407  0.68497   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.014 on 71 degrees of freedom
## Multiple R-squared:  0.002332,   Adjusted R-squared:  -0.01172 
## F-statistic: 0.1659 on 1 and 71 DF,  p-value: 0.685

Model and parameter recoverability

Memory Specificity Analyses: Experiment 2

Kate Nussenbaum

6/13/24

Import and process data

Learning

Model: Correct responses by age, trial, block number, and block condition

Figure 5A: Correct response by block condition, stimulus repetition, and age group

Supplementary Figure: Correct response by block condition and block number

Figure 5B: Generalization by block condition, category repetition, age group

Model: Correct response to first appearance of each stimulus

Model: Category win-stay lose-shift

Supplementary Figure: WSLS by age group

Supplementary Figure: WSLS by block number

Memory

Overall descriptive memory stats

Memory delay stats

Figure 5D: AUC values by age group, memory specificity, block condition

Model: AUCs by age group, reward condition, memory specificity

Model: AUCs by age, reward condition, foil type, delay

Supplementary Figure: AUC values with delay

RL modeling

Choice weights

Figure: Distribution of choice weights

Figure 5C: Choice weights box plot

Model: Choice weights by block condition and age group

Model: Exemplar choice weights by condition

Model: Category choice weights by condition

Model: Relation between exemplar and category choice weights

Relations between choice weights and points earned

Supplementary Figure: Points earned vs. beta values

Relations between learning and memory

Do points earned during learning relate to memory?

Model: AUC by points earned, reward condition, age group

Figure 5E: AUC by performance group and reward condition

Do choice weights relate to memory?

Model: AUC by age group, exemplar choice weights, specificity, block condition

Figure 5F: AUC by exemplar choice weights: model effects

Model: AUC by age group, category choice weights, specificity, block condition

Figure 5F: AUC by category choice weights: model effects

Relations between age group and other model parameters

Model: Alpha choice values by age group

Model: Alpha cf values by age group

Model: Initial Q by age

Model and parameter recoverability

Model Recoverability

Parameter recoverability (FourB_oneA_oneQ_CF)